Repsol Flagship Store, Madrid, Spain
Company overview
Repsol is a global multi energy company committed to drive the energy transition through innovation, technology and operational excellence. With more than 24,000 employees across 29 countries, the company works to provide the needed energy solutions to meet current and future energy demand.
We operate across the entire energy value chain, from oil and gas exploration and production to refining, low carbon electricity generation, and the commercialization of energy solutions for mobility, homes and industry. This integrated model combines deep industrial capabilities with a strong customer focus.
In mobility and retail, Repsol serves millions of customers every day through an extensive network (+4.000 stations) evolving from traditional fuel stations into multi service hubs where energy, convenience retail and digital services converge. These spaces integrate physical and digital experiences to deliver faster and more personalized services.
Technology and digitalization play a central role in this transformation. Through advanced analytics, AI, cloud technologies and automation, Repsol accelerates innovation across its operations. Supported by Repsol´s Technology Lab, where more than 250 experts develop solutions for the entire energy value chain.
With the ambition of becoming a net zero emissions company by 2050, Repsol continues advancing towards a more sustainable and efficient energy future.
Set the Scene
Repsol’s entry is part of a broader end to end digital transformation of its mobility retail business, redefining the role of the service station in an evolving landscape where rising customer expectations and competitive pressure make incremental digital upgrades insufficient.
In response, Repsol developed an integrated ecosystem where data, IoT and advanced analytics sit at the core of operations. This data driven model connects store infrastructure, workforce, customers and partners in real time, improving customer experience and service station operations through predictive capabilities, personalized engagement and measurable performance improvements, transforming operational data into improved products, services and customer experiences generating significant incremental contribution margin.
This technology integration already spans the value chain through more than 30 projects.
Mateo Inurria flagship store is the first full scale deployment of this strategy, designed to test and optimize solutions before scaling the model across the network through repeatable global architecture.
Innovation Overview
Repsol’s Smart Innovation is an end-to-end intelligent retail model that places the customer at the center while transforming service station operations through data driven decision making.
This is enabled by an ecosystem that combines data from our customer intelligence tool, Waylet, with a suite of integrated technologies that allow us to understand customer behavior and interactions:
| Waylet | Repsol’s digital payment and loyalty app | Provides us data from over 10 M users |
| Qualtrics | Our customer experience management platform | Captures active feedback to assess satisfaction and profile the customer journey |
| ElIoT | Our digital IoT monitoring platform | Optimizes operations through continuous sensor based tracking (equipment availability & predictive maintenance) while identifying consumption patterns to anticipate customer needs |
| Walkbase | Our in store analysis tool | Tracks customer in store activity (dwell time & in store customer journey) to optimize assortment placement and planogram decisions |
| Dynamic pricing | Our price adjustment tool | It enables real time adjustment of pricing and promotions at the point of sale based on customer data |
| AI & Gen AI | Our AI and Gen AI ecosystem | It integrates all tools to anticipate decisions and enhance both operations and customer experience |
Challenge & Opportunity
Repsol faced a structural change driven by the electrification of mobility, which is gradually reducing fuel demand and increasing the need to diversify revenue beyond traditional fuel sales. At the same time, customer expectations have evolved rapidly, with consumers demanding fast, convenient and fully digital experiences similar to those offered by digital native retailers.
However, traditional service station models were not designed for this new context. Manual processes, fragmented data and limited personalization made it difficult to optimize store performance, supply chain efficiency and customer engagement at scale.
As competition in convenience retail and mobility services intensified, differentiation based only on price or location became insufficient. This environment created an opportunity to rethink the service station as a customer centric retail platform, delivering frictionless and personalized in store experiences that increase dwell time while unlocking new revenue streams such as premium retail, services, subscriptions and retail media.
Partnerships & Ecosystem Collaboration
To deliver this transformation, Repsol has built an ecosystem of technology and commercial partners.
At its foundation, data and artificial intelligence capabilities are enabled through collaboration with partners such as NVIDIA, supporting advanced analytics, simulation and optimization to drive predictive operations and data driven decision making.
In store intelligence is powered by Walkbase, providing location based insights into customer behavior, while Scala enables real time communication and retail media activation across the store environment.
The commercial ecosystem includes assortment partners such as Coca Cola and Mondelez, alongside food service collaborations with Lizarran, Enrique Tomás, Hermanos Torres and Levaduramadre, as well as last mile delivery partners increasing convenience and dwell time.
Customer experience and loyalty are driven by Waylet, complemented by Qualtrics for continuous feedback and connected with partners such as Iberia, El Corte Inglés, Booking or eDreams.
All partners operate through a common digital retail platform enabling scaling across network.
Setup & Early Experiments
Repsol began its innovation journey with a data first approach, prioritizing understanding customer behavior before scaling solutions.
Repsol identified in Waylet a unique opportunity to leverage customer data and build a new retail model. It provided rich behavioral and transactional insights into preferences, visit frequency and engagement patterns.
To complement this data, Repsol deployed IoT sensors capturing real time information on customer journeys, movement between zones and store interactions. Combined with transaction data and Waylet profiles, these insights created a unified view of customer behavior, dwell time and purchasing patterns across the store environment.
Mateo Inurria service station in Madrid was selected as the first pilot to test this model in a real operating environment and establish a reference store for deployment. Analytics enabled experimentation with store layouts, services and digital touchpoints, helping design an optimized store ecosystem aligned with customer needs before scaling the model across the network.
Digital & Data Enablement
Technology and data are at the core of Repsol’s innovation, connecting customer experience, store operations and decision making in real time. Waylet plays a central role in this model by enabling frictionless payment through Way & Go for example, which allows customers to scan and pay from their mobile phone. Waylet also links transactions with loyalty, identification and personalization.
This customer layer connects directly with operations through ElioT, Repsol’s IoT, which strengthens the connection between infrastructure, operations and channels to build a more connected and efficient network. Combined with sensorization and advanced analytics, it enables predictive inventory replenishment and equipment performance, while sensors and heat maps track customer movement and dwell time to inform planograms and activate personalized content.
TOR extends this model beyond the physical site, while Retail Media and AI powered smart pricing further enhance commercial decisions and customer experience.
Scaling the Innovation
The transition from initial pilots to broader rollout was enabled by a standardized reference architecture designed for scale, allowing deployment across the network while adapting technologies to each store’s characteristics.
Operational processes were redesigned to support scale, shifting from manual supervision to exception based management, greater automation and data driven decision making. Workforce capabilities were standardized through targeted training, digital tools, real time alerts and clearly defined operational roles, ensuring consistent execution across locations.
This scaling model is reinforced by a Generative AI Hub that allows us to test new solutions, validate them in practice and deploy those that prove effective.
To accelerate expansion, partner integrations were standardized within a shared digital framework. Initiative prioritization is managed through homogeneous KPIs and unified criteria, while cross functional governance across retail, digital, operations and partner teams ensures alignment, clear ownership and coordinated execution as the model scales.
Operational Transformation
Repsol’s innovation has reshaped daily store operations by shifting from manual, reactive processes to real time, data driven management.
Through IoT, incidents related to equipment, refrigeration, lighting and infrastructure are automatically detected and escalated, improving responsiveness and reducing downtime.
This operational transformation has also reshaped the workforce, reducing manual workload and enabling teams to focus on higher value, exception based management supported by MOM, Repsol’s solution for managing store operations more efficiently and securely.
The same logic extends to supply chain and control. Suggested Order improves fuel and non-fuel purchasing through consumption history and intelligent inventory management, increasing availability while reducing errors and overstock. Stop Fugados strengthens control by identifying flagged vehicles linked to previous unpaid incidents before fuel dispensing.
At store level, layouts were redesigned using customer behavior and dwell time insights, improving traffic flow, category performance, customer experience and decision making.
Setbacks & Pivots
Our development created a new challenge: not only capturing big amounts of customer data, but managing it efficiently enough to support execution at scale. This became one of the most important lessons of the innovation journey.
Early attempts at hyper granular personalization generated data overload and operational complexity, making consistent execution difficult. In response, Repsol shifted toward automated store and customer clustering, balancing relevance with scalability.
Some customer journeys were also overdesigned, creating friction rather than value, and were simplified to improve clarity, usability and adoption. On the operational side, initial alerting models generated too many interruptions for staff, leading to a redesign based on alert prioritization and task automation, so human intervention focused only where it added real value.
Pilots were never treated as final solutions. Continuous iteration, testing and refinement strengthened both performance and scalability.
Impact & Results
Despite 5% reduction in fuel liters sold over the past three years due to the rapid electrification of the market, our Intelligent Store program has enabled us to stay ahead of the curve and grow beyond fuel, demonstrating a measurable impact on commercial performance, customer experience, and operations.
From a commercial perspective, the model has increased customer dwell time and made it possible to tailor products and services more effectively to customer needs. As a result, average ticket value has increased by up to 20%, driving sales growth. In addition, thanks to the combination of personalized promotions and dynamic pricing, revenues have increased up to 30%.
From an operational standpoint, automation and smart management have improved staff productivity by between 10% – 15%. This has significantly increased the efficiency of our tasks, resulting in savings of more than 300k hours. At the same time, ElioT has reduced maintenance costs.
In terms of contribution margin, our ecosystem has enabled us to increase it up to 15% through these initiatives.
Overall, these results position Mateo Inurria as a proven smart retail model with the ability to transform customer value, operational efficiency, and profitable growth across our network.
Scalability & Future Potential
The Mateo Inurria flagship was designed as a scalable reference model and is being progressively deployed across Repsol’s service station network through a standardized, modular architecture that enables rapid replication while adapting to different store formats and ownership models.
The technology roadmap expands AI-driven optimization and predictive analytics across pricing, inventory, workforce planning and energy management. Personalization will deepen through Waylet data, enabling tailored customer journeys, dynamic offers and cross-service recommendations. Digital simulations of customer behavior will increasingly inform store layouts and activate promotions based on real-time positioning and in-store context.
The ecosystem will continue expanding through standardized onboarding of gastronomy, mobility, logistics and retail media partners, while energy optimization and smart infrastructure accelerate emissions reduction and operational efficiency.
